Copy number variations with adaptive potential in caribou ( <i>Rangifer tarandus</i> ): genome architecture and new annotated genome assembly
Bibliographic record
Abstract
Abstract Background Rangifer tarandus (caribou and reindeer) has experienced recent drastic population size reductions throughout its circumpolar distribution. In efforts aimed at preserving caribou in North America and reindeer in Eurasia, genetic diversity conservation is of utmost importance, particularly the adaptive genetic diversity. To facilitate genomic studies of the caribou population, we improved genome assembly and annotation by combining long-read, linked-read and RNA sequencing technologies. As copy number variations (CNVs) are known to impact phenotype and are therefore likely to play a key role in adaptation, we investigated CNVs among the genomes of individuals representing three ecotypes of caribou (migratory, boreal and mountain). Results Using de novo transcriptome assembly and similarity with annotated human gene sequences, we identified 17,394 robust gene models embedded in a new highly contiguous genome assembly made of 13,994 scaffolds and presenting the highest N50 reported to date. A BUSCO analysis supported the high accuracy of this assembly, 90% of which being represented by only 131 scaffolds. Genome level comparisons with domestic ruminant species showed high synteny within this clade. A total of 1,698 large CNVs (length > 1kb) were identified, including 332 overlapping coding sequences annotated for functions related to immunity, musculoskeletal development or metabolism regulation and others. While the CNV distribution over the genome revealed 31 CNV hotspots, 43 large CNVs were particularly distinctive of the migratory and sedentary ecotypes and included genes annotated for functions related to cardiac development, fatty acid regulation, cold responses, locomotory behavior or environmental perception (hearing and sight), that can be related to the expected adaptations. Conclusions This work includes the first publicly available annotation of the Rangifer tarandu s genome and the first genome assembly allowing genome architecture analyses. This robust annotation based on truly expressed sequences showed a distribution overlapping many CNVs that are promising candidates given the annotations supporting their involvement in adaptation. This new highly contiguous assembly will allow relative localization of genetic variations and features and will be a valuable resource for molecular tool development and genomic studies aimed at describing and preserving this species.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".